Abstract
Casting silicone elastomers into 3D printed molds has seen a surge of applications in soft robots, soft manipulators, microfluidics, wearable technologies and stretchable sensors. In such devices, buried fluid channels are used to transport fluids, as fluidic actuators and as sensors with liquid metal. However, it is difficult to demold structures with buried channels or overhangs. As a solution, using sacrificial molds made of dissolvable materials has been proposed. In this paper, we evaluate different commercially available 3D printing materials as dissolvable mold materials. We tested dissolving prints made of high-impact polystyrene (HIPS), acrylonitrile butadiene styrene (ABS), polyvinyl butyral (PVB) and polyvinyl alcohol (PVA) in limonene, acetone, isopropanol/ethanol and water, respectively. We further studied the effect of magnetic stirring and ultrasonic bath on the dissolution times. Finally, we fabricated buried channels using different mold materials and silicone elastomers. The results show that at least ABS, PVB and PVA can be used as mold materials. In particular, PVA is a promising material as it is soluble in water. The studied method simplifies the fabrication of soft devices, allowing the fabrication of overhangs and buried channels in a single casting step.
Original language | English |
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Title of host publication | 2019 2nd IEEE International Conference on Soft Robotics (RoboSoft) |
Publisher | IEEE |
Pages | 509-513 |
Number of pages | 5 |
ISBN (Electronic) | 9781538692608 |
DOIs | |
Publication status | Published - 24 May 2019 |
Publication type | A4 Article in conference proceedings |
Event | IEEE International Conference on Soft Robotics, RoboSoft - Seoul, Korea, Republic of Duration: 14 Apr 2019 → 18 Apr 2019 |
Conference
Conference | IEEE International Conference on Soft Robotics, RoboSoft |
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Country/Territory | Korea, Republic of |
City | Seoul |
Period | 14/04/19 → 18/04/19 |
Publication forum classification
- Publication forum level 1
ASJC Scopus subject areas
- Materials Science (miscellaneous)
- Artificial Intelligence
- Mechanical Engineering
- Control and Optimization